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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM65433

Biometric Authentication Techniques: A Review of Face, Palm, and Voice Recognition with Machine Learning Approaches

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65433

Volume:

10 |

6 |

Jun 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM65433

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GS

Gaurav Shinde

Computer Engineering

RMD SINHGAD SCHOOL OF ENGINEERING

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SB

Shradhha Bhosale

Computer Engineering

RMD SINHGAD SCHOOL OF ENGINEERING

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SD

Sumeet Darje

Computer Engineering

RMD SINHGAD SCHOOL OF ENGINEERING

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RN

Rutuja Nalawade

Computer Engineering

RMD SINHGAD SCHOOL OF ENGINEERING

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Abstract

This review represent the significance of bio-metric authentication using face, palm, and voice which has become increasingly important as digital systems need reliable and robust security. Each and every method has its own ben-efits, face recognition allows fast and contactless verification, palm authentication uses unique patterns on the epidermis of palm to authenticate the user and voice recognition uses voice frequency and amplitude to authenticate. Using Deep learning and Machine Learning made these methods more accurate and robust by improving recognition of features and deal with external environmental factors like light, noise, etc.

KEYWORDS

Face Palm and Voice Recognition

Cite This Article

Gaurav Shinde, Shradhha Bhosale, Sumeet Darje, Rutuja Nalawade, "Biometric Authentication Techniques: A Review of Face, Palm, and Voice Recognition with Machine Learning Approaches," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-4, Jun 2026. https://doi.org/10.55041/IJSREM65433

Full Article/Conclusion

The review of biometric authentication shows how traditional methods was consistently converted into more advanced deep-learning techniques that improved accu-racy, security, speed, robustness and reliability. Face, palm, and Voice biometrics are overall improved by feature extraction and more efficient processing steps makes authentication effective in real-world scenarios. Even with problems like environmental changes, noise, and fake attempts this ongoing research improves biomet-ric authentication systems with better and efficient algo-rithms, improved sensing methods, and stronger security. Overall, biometric authentication is a strong and growing security method.

References

[1]   V. Hanumara, S. R. Medidi, A. P, and V. D, “Contactless Palm Recog-nition System,” Conference, pp. 1–6, May 2023, doi: 10.1109/in-cet57972.2023.10170162. [2]   D. Roy, T. N. Pandey, B. B. Dash, S. S. Patra, U. C. De, and A. Tripathy, “Intelligent Analysis and Identification of Palm Gestures using ML Algorithms,” Proc. ICCECE, pp. 1–6, Feb. 2024, doi: 10.1109/iccece58645.2024.10497373. [3]   I. Hussain, A. K. Talukdar, and K. K. Sarma, “Hand gesture recog-nition system with real-time palm tracking,” Proc. IEEE INDICON, pp. 1–6, Dec. 2014, doi: 10.1109/indicon.2014.7030571. [4]   A. Reyana, J. S. Jocelyn, and A. Priyanka, “Use of Artificial In-telligence for Palm Vein Detection-based Personal Identification,” Proc. ICCES, vol. 39, pp. 950–954, Jun. 2023, doi: 10.1109/ic-ces57224.2023.10192756. [5]   B. S. Prakoso, I. K. Timotius, and I. Setyawan, “Palmprint iden-tification for user verification based on line detection and local standard deviation,” Proc. ICITACEE, vol. 2, pp. 155–159, Nov. 2014, doi: 10.1109/icitacee.2014.7065733. [6]   N. S. Bao, Y. Y. Zhang, and J. L. Liu, “Action Recognition Based on Multidimensional Palm Action Features,” Proc. ICCSMT, vol. 28, pp. 367–374, Nov. 2022, doi: 10.1109/iccsmt58129.2022.00085. [7]   M. M. H. Ali, P. Yannawar, and A. T. Gaikwad, “Study of edge detection methods based on palmprint lines,” Proc. ICEEOT, pp. 1344–1350, Mar. 2016, doi: 10.1109/iceeot.2016.7754902. [8]   R. Salins, S. Anand, P. Nb, and T. T, “Advanced Palm Detec-tion Techniques in Forensic Science Using UVPVUP Technique,” Proc. ICETITE, vol. 92, pp. 1–6, Feb. 2024, doi: 10.1109/ic-etite58242.2024.10493722. [9]   P. N. Crisnapati, M. Setiawan, I. G. N. W. Arsa, P. D. Novayanti, M. S. Wibawa, and K. G. O. Ciptahadi, “Real-Time Hand Palm Detection and Tracking Augmented Reality Game Using Lucas Kanade Optical Flow Combined with Color Blob Detection,” Proc. ICORIS, pp. 263–268, Aug. 2019, doi: 10.1109/icoris.2019.8874892. [10]   D.  Meena  and  R.  Sharan,  “An  approach  to  face  detec-tion and recognition,” Proc. ICRAIE, pp. 1–6, Dec. 2016, doi: 10.1109/icraie.2016.7939462.

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Publication Date

6/24/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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